from typing import Optional
from collections import Counter
import plotly
import plotly.graph_objects as go
import plotly.express as px
from PIL import Image
import io
from IPython.display import display
def plotly_figure_to_image(fig, extension: str = 'png', **kwargs):
img_bytes = fig.to_image(format=extension, **kwargs)
return Image.open(io.BytesIO(img_bytes))
def save_image(image, name: str, save_dir: str = "images", extension: str="png"):
if not os.path.exists(save_dir):
os.mkdir(save_dir)
filename = "".join(i for i in name if i not in "\\/:*?<>|()- ")
filepath = f"{save_dir}/{filename}.{extension}"
image.save(filepath)
def stackedBarChartDF(
df: pd.DataFrame,
title: str,
palette: list,
diverging: bool = False,
attributes: list = ["Understandability", "Usability", "Informativeness", "Value"],
labels: Optional[list] = None,
save_fig: bool = False,
save_name: Optional[str] = None,
save_dir: str = "images",
width: int = 1200,
height: int = 400,
font: dict = {'size' : 14},
web_display: bool = False,
legend: dict=dict(
orientation="h",
yanchor="bottom",
y=-0.4,
xanchor="center",
x=0.5),
showlegend: bool=False,
**kwargs
):
counters = [Counter(df[attribute]) for attribute in attributes]
fig = go.Figure() # type: ignore
category_order = [
"Strongly<br>disagree",
"Disagree<br>",
"Slightly<br>disagree",
"Neutral<br>",
"Slightly<br>agree",
"Agree<br>",
"Strongly<br>agree",
]
number_order = [1, 2, 3, 4, 5, 6, 7]
labels = labels if labels else attributes
def add_bar_trace(num, transform, showlegend: bool = True):
rating = number_order[num]
counts = [counter[rating] for counter in counters]
total_count = sum(counters[0].values())
xvals = [transform(count) / total_count for count in counts]
fig.add_trace(
go.Bar(
x=xvals,
y=labels,
# text=counts,
# textposition='inside',
orientation="h",
name=category_order[num],
width=0.8,
marker_color=palette[num],
legendgroup=category_order[num],
showlegend=False,
) # type: ignore
)
if diverging:
# negative side
add_bar_trace(3, lambda x: x * -0.5)
for num in reversed(range(0, 3)):
add_bar_trace(num, lambda x: x * -1)
# positive side
add_bar_trace(3, lambda x: x * 0.5, showlegend=False)
for num in range(4, 7):
add_bar_trace(num, lambda x: x)
else:
for num in reversed(range(0,7)):
add_bar_trace(num, lambda x: x)
for num in reversed(range(0, 7)):
fig.add_trace(
go.Bar(
x=[0] * 7,
y=labels,
orientation="h",
name=category_order[num],
marker_color=palette[num],
legendgroup=category_order[num]
) # type: ignore
)
fig.update_layout(
barmode="relative" if diverging else "stack",
yaxis_autorange="reversed",
# title=dict(
# text=title,
# x=0.0,
# y=0.92
# ),
xaxis={"tick0": 0, "tickformat": "%", "range": [-1, 1]},
legend=legend,
showlegend=showlegend,
font=font,
autosize=False,
**kwargs
)
if not diverging:
fig.update_layout(
xaxis = {
"range" : [0, 1],
'side': 'top',
"color" : palette[-1]
},
xaxis2= {
'anchor': 'y',
'overlaying': 'x',
'side': 'bottom',
"tickformat": "%",
"range": [1, 0],
"color" : palette[0]
})
fig.data[-1].update(xaxis='x2')
im = plotly_figure_to_image(fig, width=width, height=height, validate=True)
if web_display:
fig.show()
else:
display(im)
if save_fig:
save_image(im, save_name if save_name else title, save_dir)
palette = [plotly.colors.diverging.RdBu[n] for n in [2, 3, 4, 5, 6, 7, 8]] # type: ignore
space = " " * 4
labels = [
f"I find the explanation intuitively understandable{space}",
f"The explanation helps me to understand factors relevant to the algorithm{space}",
f"The explanation helps me to decide whether I can trust the generated annotations{space}",
f"The explanation provides me with valuable information for my work{space}",
]
